Marine ecological environment monitoring system based on satellite remote sensing

Abstract

The invention relates to the technical field of marine environment remote sensing monitoring, and discloses a marine ecological environment monitoring system based on satellite remote sensing. And the receiving unit synchronously acquires vertical sections of four paths of returned signals of co-polarization elastic scattering, cross-polarization elastic scattering, laser-induced fluorescence and water body Raman scattering. A data processing unit establishes a collaborative inversion framework integrated with multiple physical constraints, and the core of the collaborative inversion framework is to construct a cost function comprising an observation constraint term and a Raman optical closed collaborative constraint term. The function is solved through an iterative optimization algorithm, and vertical sections of ecological parameters such as phytoplankton and suspended solids are inverted. According to the method, the Raman signal is taken as a physical reference, the forced inversion result is self-consistent in optics, the ill-conditioned problem in traditional inversion is effectively solved, and the accuracy and reliability of three-dimensional profile monitoring of the marine ecological environment are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of marine environment remote sensing monitoring, in particular to a marine ecological environment monitoring system based on satellite remote sensing. Background Art

[0002] The ocean is a vital component of the Earth system, and the health of its ecosystem is directly linked to global climate change, biodiversity, and human sustainable development. Therefore, large-scale, long-term, and continuous monitoring of the marine ecosystem, particularly key ecological parameters such as phytoplankton, suspended matter, and colored soluble organic matter, is of vital scientific and social significance. Satellite remote sensing technology, with its unique advantages of wide coverage and short repetition rates, has become an indispensable tool for marine ecosystem monitoring.

[0003] However, existing technologies still have several inherent limitations in achieving accurate, three-dimensional and reliable monitoring of the marine ecological environment.

[0004] First, current inversion algorithms for processing ocean remote sensing data generally face the problem of uncertainty in inversion results caused by insufficient physical constraints. Ocean water is a complex optical medium composed of multiple components. Inverting multiple unknown ecological parameters from limited remote sensing observation signals is essentially a typical ill-posed inverse problem. In the absence of sufficient and independent physical constraints, the inversion model often fails to converge to a unique, physically realistic solution. Different combinations of water component concentrations may produce very similar integrated optical signals, making it impossible for the algorithm to determine which set of solutions is the only correct one. This non-uniqueness of the solution greatly reduces the reliability and physical consistency of the monitoring results, fundamentally restricting the monitoring accuracy and stability of existing technologies.

[0005] Secondly, existing remote sensing technologies have limited ability to effectively distinguish different water components, especially when distinguishing between particulate matter components with similar optical properties, resulting in significant "optical confusion" issues. For example, certain types of phytoplankton and inorganic suspended particles may have similar absorption and scattering characteristics in certain spectral bands. Relying solely on traditional spectral intensity information often makes it difficult to effectively separate their contributions. This lack of differentiation directly leads to deviations in the accurate quantification of various ecological parameters, especially phytoplankton biomass, thereby limiting our ability to conduct refined assessments of core ecological processes such as the ocean carbon cycle and primary productivity.

[0006] Furthermore, the current mainstream commercial marine ecological remote sensing monitoring technology, such as ocean color satellite remote sensing, is essentially a passive remote sensing technology, and its detection capabilities are strictly limited to the surface or near-surface layer of the ocean. Sunlight cannot penetrate deeper water bodies, resulting in this type of technology being unable to obtain vertical structural information below the water surface, and the observation of the ocean is "two-dimensional." However, the marine ecosystem is a complete three-dimensional structure. Many key ecological processes, such as the subsurface chlorophyll maximum phenomenon occurring near the thermocline, play a decisive role in the productivity and structure of the entire marine ecosystem. Existing technologies are unable to gain insight into these underwater ecological characteristics, providing an incomplete or even one-sided understanding of marine ecosystems, which greatly hinders a comprehensive understanding of marine ecological processes and dynamics. Summary of the Invention

[0007] In response to the shortcomings of existing technologies, the present invention provides a marine ecological environment monitoring system based on satellite remote sensing, which solves the technical problem that existing satellite remote sensing technology is difficult to achieve accurate, high-resolution three-dimensional profile inversion of water ecological parameters in marine ecological environment monitoring due to insufficient physical constraints and single information dimension.

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions: A marine ecological environment monitoring system based on satellite remote sensing, comprising: a transmitting unit configured to transmit laser pulses of a preset wavelength and polarization state toward the ocean surface; a receiving unit configured to receive backscattered light returned after passing through the ocean water, and synchronously separate the backscattered light into at least four signal channels, respectively acquiring vertical profile data of a co-polarized elastic scattering signal, a cross-polarized elastic scattering signal, a laser-induced fluorescence signal, and a water Raman scattering signal; and a data processing unit connected to the receiving unit, configured to: Establishing a unified forward physical model that mathematically associates the preset vertical profiles of marine ecological parameters with the vertical profile data of the four signal channels; Based on a collaborative inversion framework integrating multiple physical constraints, the vertical profile data of the four signal channels are processed to invert the vertical profile of the marine ecological parameters.

[0009] Preferably, the emitting unit is configured to emit linearly polarized laser pulses with a central wavelength of 532 nm.

[0010] Preferably, the receiving unit includes: a telescope system for collecting the backscattered light; a polarization beam splitter, configured to separate the elastic scattering component in the backscattered light into a co-polarized elastic scattering signal and a cross-polarized elastic scattering signal; and a set of narrow-band filters for separating the laser-induced fluorescence signal and the water Raman scattering signal from the backscattered light.

[0011] Preferably, the collaborative inversion framework of the data processing unit is implemented by solving a preset cost function, the goal of which is to find a set of optimal vertical profiles of marine ecological parameters so that the difference between the signal profile simulated by the forward physical model and the actually observed signal profile is minimized.

[0012] Preferably, the cost function includes an observation constraint term , which is used to measure the difference between the simulated signal profile and the actually observed signal profile, and its mathematical form is: ; in: is the underwater depth; is the maximum detection depth; Represents one of the four signal channels: co-polarization, cross-polarization, fluorescence, and Raman; is at wavelength and depth The actual observed signal power at is the vertical profile state vector of the marine ecological parameter to be inverted; The forward physical model is based on the state vector Simulated signal power; is the weight coefficient of the corresponding channel.

[0013] 7. Preferably, the cost function also includes a Raman optical closure synergy constraint term , its mathematical form is: ; Among them, the effective attenuation profile of the observation system Calculated by the following formula: ; Where: is the underwater depth, is the maximum detection depth; At the Raman wavelength The actual observed signal power at is the satellite orbit altitude, is the refractive index of seawater; is the weight function of the constraint; is the vertical profile state vector of the marine ecological parameter to be inverted; The forward physical model is based on the state vector Calculated effective attenuation profile of the theoretical system.

[0014] Preferably, the data processing unit is configured to: introduce the Raman optical closure cooperative constraint term into the cost function, and utilize the water Raman scattering signal to constrain and calibrate the optical properties of the entire inversion system to ensure the physical consistency of the final inversion result.

[0015] Preferably, the data processing unit is further configured to calculate the particle depolarization ratio profile , which is an indicator for distinguishing different types of particulate matter, and its calculation formula is: ; Among them, the volume depolarization ratio Obtained by the following formula: ; Where: is the underwater depth; and At the laser wavelength and depth The co-polarized and cross-polarized elastic scattering signal powers observed at ; is depth The total backscatter coefficient of the particles at is output by the collaborative inversion framework; is the backscattering coefficient of pure water, which is a known constant; is the depolarization ratio of pure water, a known constant.

[0016] Preferably, the data processing unit adopts a variational assimilation method or a gradient descent optimization algorithm to iteratively minimize the cost function.

[0017] A method for monitoring marine ecological environment based on satellite remote sensing, comprising the following steps: S1. Signal acquisition step: Using a spaceborne active lidar system, laser pulses are emitted toward the ocean surface, and the returned backscattered light is synchronously received and separated into co-polarized elastic scattering signals, cross-polarized elastic scattering signals, laser-induced fluorescence signals, and water Raman scattering signals, thereby acquiring vertical profile data of these four signals. S2. Model and constraint construction step: construct a forward physical model that associates vertical profiles of marine ecological parameters with the vertical profile data of the four signals; and formulate a cost function that includes observation constraints, prior constraints, and Raman optical closure coordination constraints, wherein the Raman optical closure coordination constraints are intended to force the theoretical optical attenuation determined by the inversion parameters to be consistent with the optical attenuation measured by the Raman signal; S3, iterative inversion step: using a numerical optimization algorithm to iteratively minimize the cost function until the optimal vertical profile of the marine ecological parameter is obtained; S4, data generation step: outputting the optimal vertical profile of the marine ecological parameters as the monitoring result.

[0018] The present invention provides a marine ecological environment monitoring system based on satellite remote sensing. It has the following beneficial effects: 1. The present invention improves the accuracy and physical consistency of the inversion results of marine ecological environment parameters. When performing multi-parameter inversion, the existing technology often leads to large uncertainty in the results due to the non-uniqueness of the solution. The present invention creatively uses the Raman scattering signal of the water body as an independent physical benchmark, and requires that the theoretical optical attenuation determined by the inverted ecological parameters such as phytoplankton and suspended matter must be consistent with the actual optical attenuation revealed by the Raman signal. This design provides a powerful "optical anchor point" for the complex inversion system, effectively constrains the solution space, and ensures that the final output vertical profile of the ecological parameters is not only mathematically optimal, but also physically real and self-consistent, thereby significantly enhancing the reliability of the monitoring results.

[0019] 2. The present invention achieves efficient differentiation and accurate quantification of different ecological components in water bodies through the collaborative analysis of multiple optical signals. Traditional methods are difficult to effectively distinguish water components with similar optical properties but very different ecological significance. The system of the present invention synchronously acquires and integrates four signals with clear physical meanings: co-polarization and cross-polarization signals mainly reflect the morphological characteristics of particulate matter, thereby distinguishing phytoplankton from inorganic suspended matter; laser-induced fluorescence signals specifically indicate the biomass of phytoplankton; and Raman signals provide optical information of background water bodies. By collaboratively inverting these signals containing multi-dimensional information such as morphology, physiology, and environment within a unified framework, the present invention can more accurately attribute the observed optical properties to their correct physical sources, thereby significantly improving the ability to classify and quantify key ecological parameters.

[0020] 3. The present invention achieves unprecedented three-dimensional high-resolution monitoring of the marine ecological environment by combining active lidar detection with advanced profile inversion algorithms. Traditional passive remote sensing technologies are mostly limited to the acquisition of ocean surface information and cannot gain insight into the vertical structure underwater, resulting in a one-sided understanding of the ecosystem. The present invention adopts the method of actively emitting laser pulses and recording their echo times, which fundamentally has the ability to obtain vertical profile information of water bodies. Combined with the collaborative inversion method proposed in the present invention, the original optical signal profile can be efficiently converted into a vertical distribution profile of ecological parameters, thereby expanding the monitoring capability of satellite remote sensing from two-dimensional surface to three-dimensional space, and realizing direct detection of key ecological phenomena such as subsurface chlorophyll maximum, providing a revolutionary technical means for comprehensive and three-dimensional cognition of the marine ecological environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is a system architecture diagram of the present invention; Figure 2 Flow chart of the method of the present invention. DETAILED DESCRIPTION

[0022] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0023] Example: Please see the attached Figure 1 The embodiment of the present invention provides a marine ecological environment monitoring system based on satellite remote sensing, comprising: a transmitting unit configured to transmit laser pulses of a preset wavelength and polarization state toward the ocean surface; The transmitting unit is the source of the entire active detection system. Its core function is to generate and transmit laser pulses with specific physical properties to the ocean surface to actively stimulate the ocean water to produce information-rich backscattered optical signals for subsequent analysis.

[0024] The configuration of the transmitting unit is not an arbitrary choice; rather, it is tightly coupled and mutually supported with the overall technical concept of this invention, particularly the multi-channel signal separation of the receiving unit and the collaborative inversion framework of the data processing unit. Each of these technical features lays the physical foundation for achieving the invention's ultimate goal of distinguishing water components and obtaining vertical profiles of ecological parameters.

[0025] In a preferred embodiment, the transmitting unit is a high-performance pulsed laser system. This system is configured to generate laser pulses with high single-pulse energy. This high pulse energy is required because the laser pulses must pass through the entire atmosphere, penetrate turbid seawater to a depth of tens of meters or even deeper, and then undergo weak scattering in the water before returning to the receiving unit on the satellite platform along the reverse path. This entire process results in significant photon energy attenuation. Therefore, sufficient initial transmission energy is essential to ensure that the final return signal has a sufficient signal-to-noise ratio and can be effectively detected by the receiving unit.

[0026] Furthermore, the transmitting unit generates laser pulses with extremely narrow pulse widths. The duration of the laser pulse, or pulse width, directly determines the vertical resolution of the system during profiling. Narrower pulses correspond to shorter spatial lengths, meaning the system can resolve finer vertical structures in the ocean water column. Therefore, the use of narrow-pulse lasers is a prerequisite for accurately characterizing and analyzing thin layers, such as the subsurface chlorophyll maximum (SCM) layer.

[0027] In a specific implementation of the present invention, the laser pulse emitted by the emitting unit has a central wavelength that is preferably Preferably, the central wavelength The wavelength is set to 532nm. This choice was based on a thorough consideration of the optical properties of seawater. The 532nm wavelength lies in the blue-green spectral band, a "marine optical window" where seawater absorption and scattering are relatively low. Using lasers in this wavelength band minimizes wasted energy loss in water, thereby achieving maximum effective penetration depth into the water column. This ensures that the system can not only detect surface information but also obtain key ecological parameters in deeper waters, which is crucial for understanding the overall ecological dynamics of the ocean.

[0028] One of the most critical technical features of the transmitting unit in this embodiment is that it is precisely configured to emit laser pulses with a highly linear polarization state. The polarization state of the emitted laser is strictly controlled, and its polarization direction is known and pure. This characteristic is the core physical basis for the present invention to distinguish different particle components. This initial, reference linear polarization state will change its polarization state after scattering with various particles in the ocean water (such as phytoplankton with a nearly spherical shape, inorganic suspended matter with irregular shape, etc.), resulting in depolarization. The subsequent receiving unit measures the degree of depolarization to infer the morphology and other physical properties of the particles. Therefore, the transmitting unit provides a stable and pure initial polarization reference, which is the logical starting point for the effective operation of the entire polarization detection link. It is used for the subsequent data processing unit to calculate the particle depolarization ratio profile. Provides the necessary initial conditions.

[0029] The transmitting unit is also configured to transmit laser pulses vertically toward the ocean surface, in the direction of the satellite platform's subsatellite point, also known as the nadir direction. This vertical detection geometry simplifies the calculation of the laser's propagation path through the atmosphere and water during subsequent data processing. It also provides the most direct correspondence between photon flight time and underwater depth, facilitating high-precision depth calibration and ensuring the accuracy of the inverted ecological parameter profiles in the depth dimension.

[0030] In summary, the emitting unit in this embodiment outputs the laser pulse energy, pulse width, and center wavelength. The precise setting of its linear polarization state, in particular, produces a "functionalized" active detection signal. This signal is not a simple illumination source, but rather a carefully designed physical probe. Its various properties contribute to the effective separation of subsequent multi-channel signals and the ultimate solution of the collaborative inversion framework. It is the fundamental guarantee and physical source for achieving the overall technical effect of this invention.

[0031] A receiving unit configured to receive backscattered light returned after passing through the ocean water, and synchronously separate the backscattered light into at least four signal channels, respectively acquiring vertical profile data of a co-polarized elastic scattering signal, a cross-polarized elastic scattering signal, a laser-induced fluorescence signal, and a water Raman scattering signal; The receiving unit, the "eyes" of the active detection system, does not simply collect optical signals; rather, it functions as a sophisticated, multifunctional optical analysis and separation subsystem. It is configured to receive backscattered light from the transmitting unit, which has been complexly affected by the ocean water. In an unprecedented collaborative approach, it precisely deconstructs this weak, mixed optical signal into multiple independent, information-rich signal channels.

[0032] The overall design of the receiving unit is deeply integrated with the technical concept of the present invention. Each of its components and functions is closely linked to the characteristics of the transmitting unit and the inversion requirements of the data processing unit, together forming a complete closed loop of the technical solution of the present invention.

[0033] In a preferred embodiment, the receiving unit structurally comprises a telescope system, a polarization optical component, and a spectrum separation component, which operate in series to perform step-by-step processing and separation on the returned backscattered light.

[0034] First, the front end of the receiving unit is a large-aperture telescope system. Its function is to maximize the collection of extremely weak backscattered photons returning from the ocean. Given the extremely long distances the signal travels from the satellite to the ocean and back again, and the significant attenuation experienced by water, a large-aperture design effectively improves the system's photon capture efficiency. This is the physical basis for ensuring that all subsequent signal channels have sufficient signal-to-noise ratio (SNR) for effective analysis.

[0035] After the optical signal is collected by the telescope system, it enters the polarization optical component which is crucial in this embodiment. Preferably, this component is a polarization beam splitter with a high extinction ratio. This component is specifically designed for the wavelength of the emitted laser. The same elastic scattered light is processed. Its function is to accurately separate this part of the signal into two mutually orthogonal polarization components according to the polarization direction and guide them to different detectors: Co-polarized elastic scattering signal : The polarization direction of this signal component is parallel to the polarization direction of the linearly polarized laser emitted by the transmitting unit. It mainly carries single backscatter information caused by spherical particles in the water column (such as most phytoplankton cells).

[0036] Cross-polarized elastic scattering signal : The polarization direction of this signal component is perpendicular to the polarization direction of the emitted laser. It mainly comes from the multiple scattering process that photons experience in water, as well as depolarization scattering caused by irregular and non-spherical particles (such as mineral particles and debris).

[0037] This polarization separation design is the key to the present invention in distinguishing the particle components. It provides a direct calculation method for the volume depolarization ratio for the subsequent data processing unit. The required basic data. The ratio is obtained directly from the power of the two signals using the following formula: ; in, and At the laser wavelength and depth The co-polarized and cross-polarized elastic scattering signal powers observed at . Volume depolarization ratio It is a parameter that is extremely sensitive to the shape of particles. Therefore, by accurately acquiring these two polarization signals, the present invention provides crucial morphological constraint information for subsequent model inversion of phytoplankton and inorganic suspended matter.

[0038] After separating the polarization component of elastic scattering, the remaining inelastic scattered light in the optical path enters a spectral separation component. In one specific implementation, this component is a set of high-precision narrowband filters with precisely designed center wavelengths and bandwidths. The function of this filter set is to accurately "extract" two extremely weak inelastic scattering signals from the broad spectrum of background light, which are indicative of marine ecological research: Laser-induced fluorescence signal : With a central wavelength preferably set at about 685nm This wavelength is the characteristic fluorescence peak emitted by chlorophyll a in phytoplankton after being excited by a 532nm laser. Therefore, the intensity of this signal is directly and specifically related to the biomass and physiological activity of phytoplankton in the water body, providing a basis for the subsequent model inversion of phytoplankton concentration. Provides the most direct and least ambiguous observation constraints.

[0039] Water Raman scattering signal : With a central wavelength preferably set at about 650nm The Raman signal is separated by a filter. This signal is the characteristic scattering produced by water molecules themselves under laser excitation. Its key value lies in the fact that the number density of water molecules in seawater can be considered a constant at the detection scale. Therefore, the attenuation of the Raman signal underwater acts like a built-in "standard candle" that travels synchronously with the laser pulse. The changes in its signal intensity provide a very pure reflection of the two-way optical attenuation of the laser in water.

[0040] The precise separation and detection of Raman signals by the receiving unit is the physical prerequisite for realizing the core innovation of this invention, "Raman optical closure cooperative constraint". It provides the data processing unit with the calculation of the effective attenuation profile of the observation system. The required raw data provides an unbiased "optical anchor" derived from real physical processes for the entire complex, multi-parameter inversion system.

[0041] Finally, the four separated optical signals (co-polarization, cross-polarization, fluorescence, and Raman) are guided to their respective high-sensitivity photodetectors, and the arrival time of each photon is recorded by a high-precision timing electronics system, thereby converting the signal intensity into a depth-dependent signal. Changing vertical profile data.

[0042] In summary, the receiving unit in this embodiment, through its dual, refined separation capabilities in both polarization and spectral dimensions, successfully deconstructs a single, ambiguous, mixed return optical signal into four distinct data streams, each carrying independent information about particle morphology, phytoplankton biomass, and total water optical attenuation. It serves not only as a passive signal collector but also as an effective information preprocessor and provider of key constraints. Its functional design provides the complete and essential data support for the successful implementation of the collaborative inversion framework of this invention.

[0043] and a data processing unit connected to the receiving unit, configured to: Establish a unified forward physical model that mathematically correlates the preset vertical profiles of marine ecological parameters with the vertical profile data of the four signal channels; Based on a collaborative inversion framework integrating multiple physical constraints, the vertical profile data of the four signal channels are processed to invert the vertical profiles of marine ecological parameters.

[0044] The data processing unit is the intelligent core and central processing hub of the system. Physically connected to the receiving unit, it functionally hosts the critical algorithmic framework for multi-channel optical observations and the inversion of marine ecological parameters. This unit is more than a simple data recording or computing device; it is a dedicated processing system configured to execute a complex, coordinated inversion process involving multiple physical constraints.

[0045] In a specific embodiment, the data processing unit can be a high-performance computing platform, internally embedded or running a specific software program that implements the method of the present invention. Its workflow begins with receiving the four channels of raw signal profile data output by the unit and ends with generating geophysical marine ecological parameter products. Its internal operating logic can be broken down into the following interrelated modules.

[0046] First, the data processing unit performs data preprocessing and key constraint extraction. After receiving the four-way signal profile data from the receiving unit, the module first performs standardized distance correction to eliminate the geometric effects introduced by the changes in satellite altitude and underwater depth, and obtains a standardized observation signal profile that can purely reflect the optical characteristics of the water body. Next, the module performs a key pre-step of the present invention: In the above example, the effective attenuation profile of the observation system is directly extracted. The calculation is based on the following physical relationship: ; in, is the underwater depth, At the Raman wavelength The actual observed signal power at is the satellite orbit altitude, is the refractive index of seawater. The significance of this step is that it converts the real-world optical attenuation information contained in the Raman signal, a "standard candle," into a clear, quantifiable physical constraint parameter. This parameter will serve as the "optical anchor" of the subsequent inversion system, used to calibrate and constrain the physical authenticity of the entire inversion solution.

[0047] Secondly, the core of the data processing unit is the construction and execution of the collaborative inversion framework. The core idea of ​​this framework is to transform the difficult nonlinear inverse problem into an optimization problem with a clear goal and multiple constraints. To this end, the data processing unit is configured to construct and solve a comprehensive cost function The function is designed to find a set of optimal marine ecological parameter state vectors , the vector can simultaneously satisfy constraints from multiple aspects. In a preferred embodiment, the cost function includes at least the following items: One is the observation constraint This term ensures that the inversion result must be faithful to the actual satellite observation. The data processing unit quantifies the state vector to be inverted by the following formula Signals simulated by the forward physical model Compared with the actual observed signal The weighted square difference between: ; in, is the vertical profile state vector of the marine ecological parameter to be inverted, Represents four signal channels: co-polarization, cross-polarization, fluorescence and Raman. is the observation signal, is the theoretical signal calculated by the internal forward model, is the weight coefficient, is the maximum detection depth. By minimizing this term, the data processing unit drives the solution vector approximation to best reproduce the state of all four observation signal profiles.

[0048] Furthermore, the cost function innovatively includes a Raman optical closure synergy constraint term This is the essence of the "cooperation" concept of the present invention. The data processing unit constructs this constraint through the following formula: ; in, is the observed attenuation profile extracted from the Raman signal in the previous step, and The data processing unit is based on the state vector of the current iteration The theoretical attenuation profile calculated using the forward physical model. The introduction of this constraint mandates that the water optical attenuation, determined by the inferred phytoplankton, inorganic matter, and CDOM concentrations, must be physically consistent with the real-world optical attenuation revealed independently by the Raman signal. This design greatly enhances the robustness and physical realism of the inversion system and avoids ambiguity in the multi-parameter solution space.

[0049] In order to obtain a stable and physically reasonable solution, the cost function can also include background constraints and smoothness constraints , which are used to introduce prior information of parameters and ensure the smooth continuity of the solution on the vertical section.

[0050] After the total cost function is constructed, the data processing unit uses an advanced numerical optimization algorithm to iteratively solve it. Preferably, a variational assimilation method such as L-BFGS or a gradient descent optimization algorithm is used, starting from an initial guess profile, by iteratively calculating the gradient of the cost function to the state vector, and continuously updating the state vector along the gradient descent direction until the cost function converges to the minimum value. The final result of this process is the optimal vertical profile of the marine ecological parameters. .

[0051] Finally, the data processing unit executes the data product generation module. It will solve the optimal solution The output of the primary core products is the high vertical resolution profiles of phytoplankton, inorganic suspended matter, and CDOM absorption coefficient. In addition, the data processing unit is also configured to derive more valuable secondary products based on these primary products. For example, it is configured to calculate the particle depolarization ratio profile. , and its calculation formula is: ; Wherein, the volume depolarization ratio required for calculation is It is calculated directly from the co-polarization and cross-polarization signals measured by the receiving unit, and the total backscattering coefficient of the particles is It is calculated from the first-level products (phytoplankton and inorganic suspended matter concentrations) obtained by inversion. and is the known optical constant of pure water. This calculation process perfectly demonstrates the collaborative work between the various modules of the present invention, combining the original observations with the inversion results to generate valuable information that can indicate the differences in particle morphology and distinguish phytoplankton from mineral particles.

[0052] In summary, the data processing unit in this embodiment is the ultimate executor of the present invention's methodology. Through an inversion framework that integrates multiple physical constraints, particularly the innovative Raman optical closure cooperative constraint, it converts the multidimensional, discrete optical signals provided by the receiving unit into a physically self-consistent, information-complete three-dimensional image of marine ecological parameters, thereby achieving the core technical objectives of the present invention.

[0053] Reference Attachment Figure 2 Another embodiment of the present invention discloses a method for monitoring marine ecological environment based on satellite remote sensing, comprising the following steps: S1. Signal acquisition step: Using a spaceborne active lidar system, laser pulses are emitted toward the ocean surface, and the returned backscattered light is synchronously received and separated into co-polarized elastic scattering signals, cross-polarized elastic scattering signals, laser-induced fluorescence signals, and water Raman scattering signals, thereby acquiring vertical profile data of these four signals. S2. Model and constraint construction steps: Construct a forward physical model that relates vertical profiles of marine ecological parameters to vertical profile data of four-way signals; and formulate a cost function that includes observation constraints, prior constraints, and Raman optical closure coordination constraints. The Raman optical closure coordination constraints are designed to force the theoretical optical attenuation determined by the inversion parameters to be consistent with the optical attenuation measured by the Raman signal; S3, iterative inversion step: using numerical optimization algorithms to iteratively minimize the cost function until the optimal vertical profile of marine ecological parameters is obtained; S4. Data generation step: output the optimal vertical profile of marine ecological parameters as monitoring results.

[0054] The method of this embodiment can be used to execute the above system embodiment. Its principles and technical effects are similar and will not be described in detail here.

[0055] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A marine ecological environment monitoring system based on satellite remote sensing, characterized in that: include: a transmitting unit configured to transmit laser pulses of a preset wavelength and polarization state toward the ocean surface; a receiving unit configured to receive backscattered light returned after passing through the ocean water, and synchronously separate the backscattered light into at least four signal channels, respectively acquiring vertical profile data of a co-polarized elastic scattering signal, a cross-polarized elastic scattering signal, a laser-induced fluorescence signal, and a water Raman scattering signal; and a data processing unit connected to the receiving unit, configured to: Establishing a unified forward physical model that mathematically associates the preset vertical profiles of marine ecological parameters with the vertical profile data of the four signal channels; Based on a collaborative inversion framework integrating multiple physical constraints, the vertical profile data of the four signal channels are processed to invert the vertical profile of the marine ecological parameters.

2. The marine ecological environment monitoring system based on satellite remote sensing according to claim 1, characterized in that: The transmitting unit is configured to transmit linearly polarized laser pulses.

3. The marine ecological environment monitoring system based on satellite remote sensing according to claim 1 is characterized in that: The receiving unit includes: a telescope system for collecting the backscattered light; a polarization beam splitter, configured to separate the elastic scattering component in the backscattered light into a co-polarized elastic scattering signal and a cross-polarized elastic scattering signal; and a set of narrow-band filters for separating the laser-induced fluorescence signal and the water Raman scattering signal from the backscattered light.

4. The marine ecological environment monitoring system based on satellite remote sensing according to claim 1 is characterized in that: The collaborative inversion framework of the data processing unit is implemented by solving a preset cost function, the goal of which is to find a set of optimal vertical profiles of marine ecological parameters so that the difference between the signal profile simulated by the forward physical model and the actual observed signal profile is minimized.

5. The marine ecological environment monitoring system based on satellite remote sensing according to claim 4 is characterized in that: The cost function includes an observation constraint term , which is used to measure the difference between the simulated signal profile and the actually observed signal profile, and its mathematical form is: ； in: is the underwater depth; is the maximum detection depth; Represents one of the four signal channels: co-polarization, cross-polarization, fluorescence, and Raman; is at wavelength and depth The actual observed signal power at is the vertical profile state vector of the marine ecological parameter to be inverted; The forward physical model is based on the state vector Simulated signal power; is the weight coefficient of the corresponding channel.

6. The marine ecological environment monitoring system based on satellite remote sensing according to claim 5 is characterized in that: The cost function also includes a Raman optical closure synergy constraint term , its mathematical form is: ； Among them, the effective attenuation profile of the observation system Calculated by the following formula: ； Where: is the underwater depth, is the maximum detection depth; At the Raman wavelength The actual observed signal power at is the satellite orbit altitude, is the refractive index of seawater; is the weight function of the constraint; is the vertical profile state vector of the marine ecological parameter to be inverted; The forward physical model is based on the state vector Calculated effective attenuation profile of the theoretical system.

7. The marine ecological environment monitoring system based on satellite remote sensing according to claim 6 is characterized in that: The data processing unit is configured to: introduce the Raman optical closure cooperative constraint term into the cost function, and utilize the water Raman scattering signal to constrain and calibrate the optical properties of the entire inversion system to ensure the physical consistency of the final inversion result.

8. The marine ecological environment monitoring system based on satellite remote sensing according to claim 1 is characterized in that: The data processing unit is further configured to calculate the particle depolarization ratio profile , which is an indicator for distinguishing different types of particulate matter, and its calculation formula is: ； Among them, the volume depolarization ratio Obtained by the following formula: ； Where: is the underwater depth; and At the laser wavelength and depth The co-polarized and cross-polarized elastic scattering signal powers observed at ; is depth The total backscatter coefficient of the particles at is output by the collaborative inversion framework; is the backscattering coefficient of pure water, which is a known constant; is the depolarization ratio of pure water, a known constant.

9. The marine ecological environment monitoring system based on satellite remote sensing according to claim 4 is characterized in that: The data processing unit adopts a variational assimilation method or a gradient descent optimization algorithm to iteratively minimize the cost function.

10. A method for monitoring marine ecological environment based on satellite remote sensing, according to a system for monitoring marine ecological environment based on satellite remote sensing according to any one of claims 1 to 9, characterized in that: The following steps are involved: S1. Signal acquisition step: Using a spaceborne active lidar system, laser pulses are emitted toward the ocean surface, and the returned backscattered light is synchronously received and separated into co-polarized elastic scattering signals, cross-polarized elastic scattering signals, laser-induced fluorescence signals, and water Raman scattering signals, thereby acquiring vertical profile data of these four signals. S2. Model and constraint construction step: construct a forward physical model that associates vertical profiles of marine ecological parameters with the vertical profile data of the four signals; and formulate a cost function that includes observation constraints, prior constraints, and Raman optical closure coordination constraints, wherein the Raman optical closure coordination constraints are intended to force the theoretical optical attenuation determined by the inversion parameters to be consistent with the optical attenuation measured by the Raman signal; S3, iterative inversion step: using a numerical optimization algorithm to iteratively minimize the cost function until the optimal vertical profile of the marine ecological parameter is obtained; S4, data generation step: outputting the optimal vertical profile of the marine ecological parameters as the monitoring result.

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